Psychiatry - Research Publications
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ItemThe association between major depressive disorder, use of antidepressants and bone mineral density (BMD) in men(JMNI, 2015-06)OBJECTIVE: Both depression and use of antidepressants have been negatively associated with bone mineral density (BMD) but mainly in studies among postmenopausal women. Therefore, the aim of this study was to investigate these relationships in men. METHODS: Between 2006 and 2011, 928 men (aged 24-98 years) from the Geelong Osteoporosis Study completed a comprehensive questionnaire, clinical measurements and had BMD assessments at the forearm, spine, total hip and total body. Major depressive disorder (MDD) was identified using a structured clinical interview (SCID-I/NP). The cross-sectional associations between BMD and both MDD and antidepressant use were analyzed using multivariable linear regression. RESULTS: Of the study population, 84 (9.1%) men had a single MDD episode, 50 (5.4%) had recurrent episodes and 65 (7.0%) were using antidepressants at the time of assessment. Following adjustments, recurrent MDD was associated with lower BMD at the forearm and total body (-6.5%, P=0.033 and -2.5%, P=0.033, respectively compared to men with no history of MDD), while single MDD episodes were associated with higher BMD at the total hip (+3.4%, P=0.030). Antidepressant use was associated with lower BMD only in lower-weight men (<75-110 kg depending on bone site). CONCLUSIONS: Both depression and use of antidepressants should be taken into account as possible risk factors for osteoporosis in men.
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ItemThe Role of Health Literacy in the Treatment of Osteoporosis(WILEY, 2016-10)
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ItemGender-specific risk factors for low bone mineral density in patients taking antipsychotics for psychosis(WILEY, 2018-01)OBJECTIVE: This study examined clinical and gender-specific risk factors for low bone mineral density (BMD) in adult patients with psychotic disorders. METHODS: The study included 285 community-dwelling patients with psychotic disorders. Dual-energy X-ray absorptiometry was used to measure BMD. Clinical characteristics associated with low BMD were identified with logistic regression analysis in total population and each gender. RESULTS: Fifty-eight (20.4%) subjects had low BMD. Low BMD was more common in men and in patients with low body mass indices (BMIs), as well as in those with shorter treatment durations, those on Medicaid, and patients using serotonergic antidepressants. Logistic regression analysis revealed that low BMD was negatively associated with BMI and treatment duration and positively with gender (male) and serotonergic antidepressants use in the overall population. In men, low BMD was associated with treatment duration and BMI; in women, low BMD was associated with BMI, prolactin level, vitamin D, and serotonergic antidepressant use. CONCLUSION: Managing the risk factors associated with low BMD among patients with psychotic disorder should be done gender-specifically. Psychotropic agents should be prescribed mindful of their effects on bone, as use of these medications is a modifiable risk factor for osteoporosis in women with psychotic disorders.
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ItemGastro oesophageal reflux disease (GORD)-related symptoms and its association with mood and anxiety disorders and psychological symptomology: a population-based study in women(BMC, 2013-07-24)BACKGROUND: Psychopathology seems to play a role in reflux pathogenesis and vice versa, yet few population-based studies have systematically investigated the association between gastro-oesophageal reflux disease (GORD) and psychopathology. We thus aimed to investigate the relationship between GORD-related symptoms and psychological symptomatology, as well as clinically diagnosed mood and anxiety disorders in a randomly selected, population-based sample of adult women. METHODS: This study examined data collected from 1084 women aged 20-93 yr participating in the Geelong Osteoporosis Study. Mood and anxiety disorders were identified using the Structured Clinical Interview for DSM-IV-TR Research Version, Non-patient edition (SCID-I/NP), and psychological symptomatology was assessed using the General Health Questionnaire (GHQ-12). GORD-related symptoms were self-reported and confirmed by medication use where possible and lifestyle factors were documented. RESULTS: Current psychological symptomatology and mood disorder were associated with increased odds of concurrent GORD-related symptoms (adjusted OR 2.1, 95% CI 1.3-3.5, and OR 3.0, 95% CI 1.7-5.6, respectively). Current anxiety disorder also tended to be associated with increased odds of current GORD-related symptoms (p = 0.1). Lifetime mood disorder was associated with a 1.6-fold increased odds of lifetime GORD-related symptoms (adjusted OR 1.6, 95% CI 1.1-2.4) and lifetime anxiety disorder was associated with a 4-fold increased odds of lifetime GORD-related symptoms in obese but not non-obese participants (obese, age-adjusted OR 4.0, 95% CI 1.8-9.0). CONCLUSIONS: These results indicate that psychological symptomatology, mood and anxiety disorders are positively associated with GORD-related symptoms. Acknowledging this common comorbidity may facilitate recognition and treatment, and opens new questions as to the pathways and mechanisms of the association.
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ItemStatin use and risk of depression: a Swedish national cohort study(BMC, 2014-12-04)BACKGROUND: Statin medications, used to prevent heart disease by reducing cholesterol, also reduce inflammation and protect against oxidative damage. As inflammation and oxidative stress occur in depression, there is interest in their potential to reduce depression risk. We investigated whether use of statin medications was associated with a change in the risk of developing depression in a very large Swedish national cohort (n = 4,607,990). METHODS: National register data for adults ≥40yr was analyzed to obtain information about depression diagnoses and prescriptions of statin medications between 2006 and 2008. Associations were tested using logistic regression. RESULTS: Use of any statin was shown to reduce the odds of depression by 8% compared to individuals not using statin medications (OR = 0.92, 95% CI, 0.89-0.96; p < 0.001). Simvastatin had a protective effect (OR = 0.93, 95% CI, 0.89-0.97; p = 0.001), whereas atorvastatin was associated with increased risk of depression (OR = 1.11, 95% CI, 1.01-1.22; p = 0.032). There was a stepwise decrease in odds ratio with increasing age (OR ≥ 40 years = 0.95, OR ≥ 50 years = 0.91, OR ≥ 60 years = 0.85, OR ≥ 70 years = 0.81). CONCLUSIONS: The use of any statin was associated with a reduction in risk of depression in individuals over the age of 40. Clarification of the strength of these protective effects, the clinical relevance of these effects and determination of which statins are most effective is needed.
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ItemPop, heavy metal and the blues: secondary analysis of persistent organic pollutants (POP), heavy metals and depressive symptoms in the NHANES National Epidemiological Survey(BMJ PUBLISHING GROUP, 2014)OBJECTIVES: Persistent environmental pollutants, including heavy metals and persistent organic pollutants (POPs), have a ubiquitous presence. Many of these pollutants affect neurobiological processes, either accidentally or by design. The aim of this study was to explore the associations between assayed measures of POPs and heavy metals and depressive symptoms. We hypothesised that higher levels of pollutants and metals would be associated with depressive symptoms. SETTING: National Health and Nutrition Examination Survey (NHANES). PARTICIPANTS: A total of 15 140 eligible people were included across the three examined waves of NHANES. PRIMARY AND SECONDARY OUTCOME MEASURES: Depressive symptoms were assessed using the nine-item version of the Patient Health Questionnaire (PHQ-9), using a cut-off point of 9/10 as likely depression cases. Organic pollutants and heavy metals, including cadmium, lead and mercury, as well as polyfluorinated compounds (PFCs), pesticides, phenols and phthalates, were measured in blood or urine. RESULTS: Higher cadmium was positively associated with depression (adjusted Prevalence Ratios (PR)=1.48, 95% CI 1.16 to 1.90). Higher levels of mercury were negatively associated with depression (adjusted PR=0.62, 95% CI 0.50 to 0.78), and mercury was associated with increased fish consumption (n=5500, r=0.366, p<0.001). In addition, several PFCs (perfluorooctanoic acid, perfluorohexane sulfonic acid, perfluorodecanoic acid and perfluorononanoic acid) were negatively associated with the prevalence of depression. CONCLUSIONS: Cadmium was associated with an increased likelihood of depression. Contrary to hypotheses, many of persistent environmental pollutants were not associated or negatively associated with depression. While the inverse association between mercury and depressive symptoms may be explained by a protective role for fish consumption, the negative associations with other pollutants remains unclear. This exploratory study suggests the need for further investigation of the role of various agents and classes of agents in the pathophysiology of depression.
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ItemInto the Bowels of Depression: Unravelling Medical Symptoms Associated with Depression by Applying Machine-Learning Techniques to a Community Based Population Sample(PUBLIC LIBRARY SCIENCE, 2016-12-09)BACKGROUND: Depression is commonly comorbid with many other somatic diseases and symptoms. Identification of individuals in clusters with comorbid symptoms may reveal new pathophysiological mechanisms and treatment targets. The aim of this research was to combine machine-learning (ML) algorithms with traditional regression techniques by utilising self-reported medical symptoms to identify and describe clusters of individuals with increased rates of depression from a large cross-sectional community based population epidemiological study. METHODS: A multi-staged methodology utilising ML and traditional statistical techniques was performed using the community based population National Health and Nutrition Examination Study (2009-2010) (N = 3,922). A Self-organised Mapping (SOM) ML algorithm, combined with hierarchical clustering, was performed to create participant clusters based on 68 medical symptoms. Binary logistic regression, controlling for sociodemographic confounders, was used to then identify the key clusters of participants with higher levels of depression (PHQ-9≥10, n = 377). Finally, a Multiple Additive Regression Tree boosted ML algorithm was run to identify the important medical symptoms for each key cluster within 17 broad categories: heart, liver, thyroid, respiratory, diabetes, arthritis, fractures and osteoporosis, skeletal pain, blood pressure, blood transfusion, cholesterol, vision, hearing, psoriasis, weight, bowels and urinary. RESULTS: Five clusters of participants, based on medical symptoms, were identified to have significantly increased rates of depression compared to the cluster with the lowest rate: odds ratios ranged from 2.24 (95% CI 1.56, 3.24) to 6.33 (95% CI 1.67, 24.02). The ML boosted regression algorithm identified three key medical condition categories as being significantly more common in these clusters: bowel, pain and urinary symptoms. Bowel-related symptoms was found to dominate the relative importance of symptoms within the five key clusters. CONCLUSION: This methodology shows promise for the identification of conditions in general populations and supports the current focus on the potential importance of bowel symptoms and the gut in mental health research.
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ItemFusing Data Mining, Machine Learning and Traditional Statistics to Detect Biomarkers Associated with Depression(PUBLIC LIBRARY SCIENCE, 2016-02-05)BACKGROUND: Atheoretical large-scale data mining techniques using machine learning algorithms have promise in the analysis of large epidemiological datasets. This study illustrates the use of a hybrid methodology for variable selection that took account of missing data and complex survey design to identify key biomarkers associated with depression from a large epidemiological study. METHODS: The study used a three-step methodology amalgamating multiple imputation, a machine learning boosted regression algorithm and logistic regression, to identify key biomarkers associated with depression in the National Health and Nutrition Examination Study (2009-2010). Depression was measured using the Patient Health Questionnaire-9 and 67 biomarkers were analysed. Covariates in this study included gender, age, race, smoking, food security, Poverty Income Ratio, Body Mass Index, physical activity, alcohol use, medical conditions and medications. The final imputed weighted multiple logistic regression model included possible confounders and moderators. RESULTS: After the creation of 20 imputation data sets from multiple chained regression sequences, machine learning boosted regression initially identified 21 biomarkers associated with depression. Using traditional logistic regression methods, including controlling for possible confounders and moderators, a final set of three biomarkers were selected. The final three biomarkers from the novel hybrid variable selection methodology were red cell distribution width (OR 1.15; 95% CI 1.01, 1.30), serum glucose (OR 1.01; 95% CI 1.00, 1.01) and total bilirubin (OR 0.12; 95% CI 0.05, 0.28). Significant interactions were found between total bilirubin with Mexican American/Hispanic group (p = 0.016), and current smokers (p<0.001). CONCLUSION: The systematic use of a hybrid methodology for variable selection, fusing data mining techniques using a machine learning algorithm with traditional statistical modelling, accounted for missing data and complex survey sampling methodology and was demonstrated to be a useful tool for detecting three biomarkers associated with depression for future hypothesis generation: red cell distribution width, serum glucose and total bilirubin.
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ItemPrior fracture as a risk factor for future fracture in an Australian cohort(SPRINGER LONDON LTD, 2015-02)SUMMARY: This study investigated the influence of prior fracture on the risk of subsequent fracture. There was a higher risk of subsequent fracture in both young and older adult age groups when Australian males or females had already sustained a prior fracture. Fracture prevention is important throughout life for both sexes. INTRODUCTION: The purpose of this study was to determine the impact of prior fracture on the risk of subsequent fracture across the adult age range in Australian males and females. METHODS: All-cause fractures were grouped into age categories for males and females enrolled in the Geelong Osteoporosis Study (Australia) using retrospective self-report data and prospective radiology-confirmed data. For all age categories, the relative risk (RR and 95% confidence interval (CI)) of subsequent fracture in a later age category was compared between those with prior fracture and those without. RESULTS: For both sexes, childhood fracture increased the risk of subsequent fracture in adolescence (males: RR 21.7; 95% CI 16.0, 27.4; females: RR 8.1; 3.5, 12.8). Males with adolescent fracture had increased risk of subsequent fracture in early adulthood (RR 11.5; 5.7, 17.3) and mid-adulthood (RR 13.0; 6.3, 19.7). Additionally, males with young adulthood or mid-adulthood fracture had increased risk of subsequent fracture in the following age group (RR 11.2; 4.4, 17.9, and RR 6.2; 0.8, 11.7, respectively). Mid-adult fractures increased the risk of subsequent fracture in older adulthood (RR 6.2; 0.8, 11.7). Females with childhood or adolescent fracture had an increased risk of fracture in young adulthood (RR 4.3; 0.7, 7.9, and RR 10.5; 4.4, 16.6), and prior fracture in older adult life increased the risk of subsequent fracture in old age (RR 14.9; 6.4. 23.3). CONCLUSIONS: Fracture prevention strategies may be more effective if attention is directed towards individuals with prior fracture at any age as they have a higher likelihood of sustaining a subsequent fracture later in life.
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ItemFractures in indigenous compared to non-indigenous populations: A systematic review of rates and aetiology.(Elsevier BV, 2017-06)BACKGROUND: Compared to non-indigenous populations, indigenous populations experience disproportionately greater morbidity, and a reduced life expectancy; however, conflicting data exist regarding whether a higher risk of fracture is experienced by either population. We systematically evaluate evidence for whether differences in fracture rates at any skeletal site exist between indigenous and non-indigenous populations of any age, and to identify potential risk factors that might explain these differences. METHODS: On 31 August 2016 we conducted a comprehensive computer-aided search of peer-reviewed literature without date limits. We searched PubMed, OVID, MEDLINE, CINAHL, EMBASE, and reference lists of relevant publications. The protocol for this systematic review is registered in PROSPERO, the International Prospective Register of systematic reviews (CRD42016043215). Using the World Health Organization reference population as standard, hip fracture incidence rates were re-standardized for comparability between countries. RESULTS: Our search yielded 3227 articles; 283 potentially eligible articles were cross-referenced against predetermined criteria, leaving 27 articles for final inclusion. Differences in hip fracture rates appeared as continent-specific, with lower rates observed for indigenous persons in all countries except for Canada and Australia where the opposite was observed. Indigenous persons consistently had higher rates of trauma-related fractures; the highest were observed in Australia where craniofacial fracture rates were 22-times greater for indigenous compared to non-indigenous women. After adjustment for socio-demographic and clinical risk factors, approximately a three-fold greater risk of osteoporotic fracture and five-fold greater risk of craniofacial fractures was observed for indigenous compared to non-indigenous persons; diabetes, substance abuse, comorbidity, lower income, locality, and fracture history were independently associated with an increased risk of fracture. CONCLUSIONS: The observed paucity of data and suggestion of continent-specific differences indicate an urgent need for further research regarding indigenous status and fracture epidemiology and aetiology. Our findings also have implications for communities, governments and healthcare professionals to enhance the prevention of trauma-related fractures in indigenous persons, and an increased focus on modifiable lifestyle behaviours to prevent osteoporotic fractures in all populations.